Abstract
An adaptive intrusion detection algorithm which combines the Adaptive Resonance Theory(ART) with the Concept Vector and the Mecer-Kernel is presented. Compared to the supervised- and the clustering-based Intrusion Detection Systems(IDSs), our algorithm can detect unknown types of intrusions in on-line by generating clusters incrementally. © Springer-Verlag Berlin Heidelberg 2006.
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CITATION STYLE
Lee, H., Chung, Y., & Park, D. (2006). An adaptive intrusion detection algorithm based on clustering and kernel-method. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3918 LNAI, pp. 603–610). Springer Verlag. https://doi.org/10.1007/11731139_70
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